Artificial Intelligence techniques and Internet of things sensors for tool condition monitoring in milling: A review

Milling is a machining process that involves removing material from a workpiece using a rotating cutting tool. During the milling process, the cutter is affected by a progressive degradation due to the grinding of the workpiece which results in a decline in product quality and a sharp increase in energy consumption and production costs. For these reasons, Tool Condition Monitoring has emerged as the essential approach in the machining industry. The application of Artificial Intelligence (AI) systems that incorporate the use of various Internet of Things sensors (IoT) to support the tool condition monitoring in the milling process has recently been a subject of great interest to researchers. It helps to achieve goals required in the modern manufacturing industries in terms of sustainability, cost reduction, and quality improvement. This review article focuses on the application of IoT sensors for recording acoustic emissions, to conduct tool condition monitoring of the milling cutting tools based on AI techniques. The discussion includes an analysis of the principal sensory systems and their main advantages and disadvantages for the milling process. Moreover, trends and problems of applied AI techniques for tool condition monitoring are highlighted.